AI and Cybersecurity in 2024: The Future Looks Bright

Did you know that every second, 39 accounts witness a cyberattack?

As a result, companies try everything to protect their data, systems, and networks from malicious software. That’s why many companies rely on artificial intelligence (AI) to manage their cybersecurity. 

The horde of advancements in the artificial intelligence (AI) space promises a exciting cybersecurity roadmap in 2024. 

In the past few years, AI has become a central cybersecurity strategy. Given the rise of concerns, understanding what to expect from AI regarding opportunities and the software it delivers can reduce your risk.

AI will prevent credential harvesting attacks

Security practitioners use AI to detect and mitigate online attacks. Yet the same technology is used by criminals in credential harvesting attacks. With the help of AI, cyber criminals illegally gain access to confidential data, like user account credentials and personal data.

Companies can use these AI methods to prevent such attacks:

  • Detects phishing attacks: Machine learning algorithms easily analyze and detect anomalies in your website and emails to identify potential attacks. For instance, an AI system detects a malicious email based on a suspicious link or attachment. This early detection prevents your customers from revealing their credentials.
  • Identifies fake websites: In 2024, more and more companies will use AI to identify fake websites, mimicking the original ones. Such websites trick your users into entering their credentials, which attackers later use for cyber fraud. Companies use Convolutional Neural Networks (CNN), a type of deep learning to identify manipulated images on phishing websites and within email content. These CNNs have advanced image recognition capable of identifying fake and manipulated images that go unnoticed by the naked eye.
  • Detects anomalies: AI-powered systems easily monitor user logins to sensitive resources to detect abnormal behavior. For instance, when a user login from a different IP address, device, or operating system, AI systems detect potential cyber-attacks by comparing these behaviors with the customer’s normal behavior.

AI will meet compliance and regulations

In 2024, data compliance is still challenging for many companies. Today, companies use AI-powered tools like Data Subject Access Request (DSAR) software to comply with regulations.

Using the DSAR software, you manage the user data requests. As most DSAR uses AI technology, it helps you handle large data requests. 

Before the DSAR software, you manually searched for the user’s information and managed it using a spreadsheet. Apart from being a cumbersome process, it was time-consuming, especially if you had to perform DSAR on thousands of user data.

But with DSAR software, you receive the following benefits:

  • Provides automated request processing: This software automates the process of DSAR. The automation primarily includes receiving requests, verifying the requestor’s identity, locating the relevant data, and providing the requested information in a secure and timely manner.
  • Improves data security: Many AI-enabled DSAR software reduces the need to handle sensitive data manually, increasing data security. It also ensures that only authorised people can access the data. 
  • Ensures compliance with regulations: Many DSAR uses AI-backed regulatory intelligence to promote data collection and processing. This feature ensures compliance with the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). 
  • Maintains audit reports: AI helps you remain audit-ready by keeping the record for all the DSAR and the responses. Because of this, it becomes challenging for users to file non-compliance complaints against you. You even show the regulatory bodies that you comply with all the data protection laws. 

AI will help with vulnerability management

Another area where AI is likely to win more laurels is vulnerability management. It provides opportunities to deliver improved outcomes, ensuring superior security against potential online attacks. Here’s how AI will help with vulnerability management:


  • Provides efficient threat detection in cloud platforms: Cloud platforms are prone to numerous security breaches because of the large amount of data they store. That’s why companies use AWS vulnerability scanning to identify and address security weaknesses before cybercriminals exploit them. Using various AI algorithm tools, these scanning tools permit continuous monitoring and ensure instant analysis. This ensures companies stay ahead of the new threats.
  • Ensures continuous monitoring and detection: AI-based systems provide continuous monitoring and detection of potential vulnerabilities and threats. This real-time approach ensures you identify and address vulnerabilities as soon as they crop up. As a result, the window of exposure to cybercriminals reduces manifolds.
  • Focuses on patch management: Leading patch management systems use advanced algorithms and AI technologies to assess vulnerabilities and prioritise risks. These AI-enabled systems prioritise risks based on severity level, patch type, and system configuration. Apart from identifying vulnerabilities, these systems suggest ways to reduce potential online attacks. In short, these AI-enabled systems provide stability to your complex IT environment.
  • Helps in sentiment analysis to detect vulnerabilities: One noteworthy feature of AI is the ability to analyse vast amounts of content. These AI tools can collect data from various sources, analyse it, and detect vulnerability trends. As a result, you’re better at understanding the potential risks associated with given vulnerabilities. AI technologies like Natural Language Processing (NLP) and Neural Networks can easily identify positive and negative sentiments from the data collected and interpret the meaning of different texts to identify potential vulnerabilities.

AI will help in intrusion detection

Another area AI will likely contribute is intrusion detection. This process identifies unauthorized and malicious activities in a computer system or network. Modern businesses use AI tools like Intrusion Detection Software or IDS to decrease intrusion detection. This software uses machine learning to learn from the traffic pattern within your network or system. As a result, IDS develops a strong defense mechanism against complex attacks.

Interestingly, IDS detects zero-day attacks that previously went unnoticed.  These systems provide real-time monitoring and give you real-time updates on potential threats. As a result, you mitigate security incidents and reduce your incident response time. 

What’s more interesting is that these AI-enabled IDS help you with deep packet inspection, signature-based detection, and cloud integration, adding an extra layer of security to your business.

With IDS, you receive proactive and adaptive defence against online attacks, helping you meet your cybersecurity goals.

AI will help in access control and authentication

Biometric authentication using fingerprints, IRIS scanners, and facial recognition is a must-have for digital users. However, these features often allow cybercriminals to enter your company’s network or system.

That’s where AI steps in.

Companies rely on various AI technologies to recognize patterns and detect and interpret unusual behaviour. 

AI can use complex algorithms and machine learning techniques to identify users based on their characteristics, such as IRIS, fingerprints, and facial features. As these biometrics are impossible to replicate, AI provides you with high security.


AI even uses historical behaviour and other factors to determine if the login attempt was genuine or a cybercriminal was trying to gain access. 

Another reason why companies are adopting AI in access control and authentication is its ability to evaluate access requests in real-time. AI authenticates a user only after cross-verifying multiple factors, such as location, time of day, and user behaviour.

  1. AI will use honeypots and other luring tactics

AI is slowly gaining traction in deception technologies. These technologies use fake information systems to attract hackers into revealing themselves. In the coming years, AI will help more in deception and identify threat actors.

AI-powered honeypots are a cybersecurity mechanism designed to attract cybercriminals from the target. A honeypot replicates the target system to understand the hacker’s techniques and origin. 

AI-powered honeypots can even lure hackers into a simulated environment to decode their components and coding techniques used to gain access to critical information. The insights gained from these luring tactics help you take robust cybersecurity measures.

Another reason deception technologies use AI is the ability of AI models to evolve and adapt their deceptive element to remain up-to-date and convincing against sophisticated and highly technical hackers.

Using AI for a secure future

The use of AI opens up numerous fields for the cybersecurity world. From DSAR software to credential harvesting attacks and from vulnerability management to intrusion detection, AI can mitigate attacks and make your system or network more secure.

The impact of AI on cybersecurity will only continue to rise, probably manifolds in the coming years.  Apart from offering a secure landscape, these six AI technologies will give you much-needed peace of mind.

With AI, the future of cybersecurity is not just promising, it’s transformative in every aspect.

Which AI-enabled technologies are you using to protect your networks and systems?